Triple
T18125267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Izumisano |
E433855
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Jeju City |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Jeju City | Statement: [Izumisano, hasSisterCity, Jeju City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeju City Context triple: [Izumisano, hasSisterCity, Jeju City]
-
A.
Jeju City
chosen
Jeju City is the capital and largest city of South Korea’s Jeju Island, known for its volcanic landscapes, tourism, and role as a regional transportation and cultural hub.
-
B.
Gijeon
Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
-
C.
Changwon
Changwon is a major industrial and administrative city in South Gyeongsang Province, South Korea, known for its planned urban layout and role as a regional government and manufacturing hub.
-
D.
Jinju-si
Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
-
E.
Gunsan
Gunsan is a coastal city in North Jeolla Province, South Korea, known for its port, industrial facilities, and longstanding association with nearby military air operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dded1bd4819080fa362e88c921cf |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.